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Shilling attack detection method based on stack type sparse self-encoder

A sparse autoencoder and attack detection technology, which is applied in the field of information security, can solve problems such as difficult to deal with trust attacks

Active Publication Date: 2016-03-09
XIDIAN UNIV
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AI Technical Summary

Problems solved by technology

However, in the traditional classified trolling attack detection algorithm, it is difficult to deal with more types of trolling attacks

Method used

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  • Shilling attack detection method based on stack type sparse self-encoder
  • Shilling attack detection method based on stack type sparse self-encoder
  • Shilling attack detection method based on stack type sparse self-encoder

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Embodiment Construction

[0021] refer to figure 1 , the implementation steps of the present invention are as follows:

[0022] Step 1, input scoring dataset.

[0023] The scoring data set is divided into a large number of unknown types of users and a small number of known types of users, both of which include trusted users and normal users, and the entire scoring data is R=|D|×|I|, where R refers to the scale of The rating matrix of D|×|I|, D refers to all users, I refers to all items, |D| and |I| refer to the number of D and I respectively, and D=D U ∪D 1 ∪…∪D q ∪…∪D c , 1≤q≤c, where D U refers to a collection of users of unknown type, D q refers to the known set of q-type users, and c refers to the total number of known user types;

[0024] Step 2, normalize the scoring matrix R.

[0025] When users evaluate items, since the scoring scales of each user are different, for example, for their favorite items, some users will give full marks, while some users will only give average marks, which w...

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Abstract

The invention discloses a shilling attack detection method based on a stack type sparse self-encoder. The shilling attack detection method is mainly used for solving the problem that corresponding characteristics of shilling attack users of different types need to be extracted in the prior art. The shilling attack detection method comprises the following steps: (1) inputting an initial scoring data set; (2) initializing the initial scoring data set; (3) directly using the score of each user as input to train the stack type sparse self-encoder, and extracting characteristic data of the user; (4) using the extracted characteristic data as input to train a Naive Bayes classifier; and (5) calculating the probability of a user with an unknown type belonging to each type according to the trained Naive Bayes classifier, and finding out the shilling attack user. The shilling attack detection method disclosed by the invention can be used for directly using the stack type sparse self-encoder to extract the characteristic data of each user, can be used for stably detecting shilling attack users of a plurality of types and can be used for detecting malicious attack users in an Internet system.

Description

technical field [0001] The invention belongs to the field of information security, and in particular relates to a troll attack detection method, which can be used to detect malicious attack users in an Internet system. Background technique [0002] At the end of the 20th century, the Internet began to sprout. With the rapid growth of the amount of information on the Internet, it takes a lot of energy for people to find the information they need online. It is this demand that gave birth to the establishment of Yahoo! Portals bring well-being to people. However, it didn't take long before the amount of information in the whole society began to grow exponentially, and it became difficult for portal websites to handle such a large-scale content. Google came into being, and the search business perfectly solved the problem of finding the content you need in massive amounts of information, and began its golden period of development. Entering the 21st century, with the further pop...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F21/55G06K9/62
CPCG06F21/552G06F2221/034G06F18/24155
Inventor 马文萍马进焦李成马晶晶闻泽联任琛
Owner XIDIAN UNIV
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